Youll have to forgive me, folks. Im in the midst of writing a paper (*insert excited Peter Griffin gasp here*– there are lots of open access virology journals, but I cant promise it).

Writing this paper has reminded me of a luxury we have in scientific research: we can be wrong.

Its bad when a physician or nurse is wrong, giving the wrong diagnosis or a wrong drug.

Its bad when a truck driver is wrong, delivering the wrong thing to the wrong place under the wrong shipping conditions.

Its bad when a teacher is wrong, mixing up a battle date or equation or artist (I hated when my teachers/profs messed up, even when they immediately recognized it, cause I would always remember the wrong thing and not the right thing for the rest of the semester!!!).

Its bad when an engineer is wrong, sending an interplanetary probe millions of miles off target.

But as a research scientist, I can be wrong as much as I damn well please. My hypothesis four years ago turned out to be completely and utterly wrong. For a while now, Ive been pretty hangdog, dragging my feet writing this paper, cause I thought I messed up. I thought I was a friggen idiot because my experiments were not matching up to my original hypothesis… they actually pointed towards the opposite of my original hypothesis… ugh…

After talking with Bossman about it, we realized that what I found is exactly what we should have expected. In retrospect, my data makes perfect sense. But if we knew four years ago what we knew now, the experiments would have been pointless!

It doesnt matter in the slightest that I was wrong four years ago– we now know the original hypothesis is wrong, and we have lots and lots of data to explain exactly why that hypothesis is wrong and to point us towards new cool experiments!

The original hypothesis was really just a starting off point. End the end, it doesnt matter whether I was wrong or right, only that our understanding of how HIV-1 works is going to increase after I publish!

My current students are of the proper age that I can, for right now anyway, use a much more plebeian source: The Magic School Bus. Our class motto is shamelessly cribbed from Ms. Frizzle–“Take Chances! Make Mistakes!”

Nice post. Encourages me to get my teeth into my diss again, and just make it really clearly wrong. (-:

It’s a PITN to figure out that one has been wrong with a long-held hypothesis, but then it’s now wrong and done! Can you give us a short rundown of the paper? Or (if that’s in the pipeline to publication) can you point us to the hypothesis you know know to be wrong?

I hope you’ll forgive me for dropping a big ol’ quote on the page and pretending I’m contributing something, but this reminds me of one of my favorite passages from Cosmos:

There are many hypotheses in science that are wrong. That’s perfectly all right; it’s the aperture to finding out what’s right. Science is a self-correcting process. To be accepted, new ideas must survive the most rigorous standards of evidence and scrutiny. The worst aspect of the Velikovsky affair is not that many of his ideas were wrong or silly or in gross contradiction to the facts; rather, the worst aspect is that some scientists attempted to suppress Velikovsky’s ideas. The suppression of uncomfortable ideas may be common in religion or in politics, but it is not the path to knowledge and there is no place for it in the endeavor of science. We do not know beforehand where fundamental insights will arise from about our mysterious and lovely solar system, and the history of our study of the solar system shows clearly that accepted and conventional ideas are often wrong and that fundamental insights can arise from the most unexpected sources.

Exactly! The great thing about science that the anti-science crew will NEVER understand is that science has nothing to do with who is “right” or “Wrong”.

It has everything to do with figuring out the best hypothesis to describe the data!

When your hypothesis fits the data, it is right. When it doesn’t, it is wrong.
A quick, non-science, slightly-over-the-top example:
Now, it is very “Right” to say that the Holocaust happened, because all of the evidence indicated that it did. Thus, this “hypothesis” is right. However, there is a possibility that it did not, however small. If in 20 years, it turns out that basically everyone on Earth was working together to fool you into thinking the Holocaust happened, and all of the evidence you previously looked at turns out to be false, then your hypothesis changes. It is then “right” to say that the Holocaust did not happen.

A wrong hypothesis is not a failure, but simply another step in the scientific method. There are no absolute rights and wrongs in science, but only “more likely to be right or wrong based on the evidence”‘s.

It’s not always so bad for an engineer to be wrong. For many years I was the sole programmer and digital designer for my company. If somebody found a problem we’d stop shipping – crisis! – and if it turned out that it was a bug in the program, I could fix it in minutes, release a new version, and the crisis was over.

I was a hero because I made a mistake! (I swear I never did this on purpose.) In this case there were strong incentives to admit the error and nearly no downside.

How the heck are you going to find new and unexpected things (i.e. interesting and really useful stuff) if every experiment does what you think it should?

What would be the point in experiment at all.

The great thing about good experiments is that the universe gets a chance to tell us a little about how stuff really works, instead of how we think they might work.

I remember saying to my PhD supervisor, who was lamenting a couple of months spent doing something that in retropsect wasn’t a great idea, since we had just found a much better approach.

I wasn’t sad at all (even though he’d only ten minutes earlier tossed a paper I’d spent weeks writing in the trash, unread). As I told him, we wouldn’t have come up with this great idea if we hadn’t worked so hard on that less great one – we needed to do that so we could do this.

Congratulations, Abbie. The first paper is always the hardest! And in a field as competitive as the one you’re in, I can’t imagine what the peer review process will be like.

Erm. I guess I shouldn’t discourage you further.

Me, I’m in a piddly-assed field most people don’t care about, and the ones that DO care absolutely HATE my lab’s working model. They DESPISE it and want to kill it in a ditch. So I’m pretty free to blab my heart out at meetings about my private hypotheses and preliminary data, because I’m pretty sure I and my boss are the only ones who’ll follow up on them. And that’s fine, because I have no self control, and I just love to gab about what I do.

The downside is the peer review process is STILL an effing pain, especially for my last paper. Ugh. But it finally saw print this week, hooray!

Yet, on the other other hand, my paper (which is awesome) shows some pretty clear data regarding how *all* of us can be right simultaneously, which is a pretty neat trick. But it means I’ll have to be more careful at meetings from now on.

“Fail early, fail often.” Basic management advice also applied to software development: avoiding failure altogether is impossible and even trying to is expensive (time, resources.) Better to accept that many-to-most of your best ideas will fail and make them fail early and cheap so you can move on.

It IS a luxury to have your hypothesis be wrong! Something similar happened to me, and I’ve found that it always goes over well at conferences when I say, “we thought that things would go this way, but in fact the exact opposite happened!” Audiences love scientists who can laugh at themselves and admit when they’re wrong. You’re telling a better story, you come off as honest and trustworthy…win/win!

There’s one frame of mind (from cybernetics) that defines “information” as “data that cannot be predicted”. E.g., if I take my current understanding of the world and say, “The sun will rise in the east tomorrow at 6:35 am local time,” and it does, I’ve learned nothing: my existing view of the world is not changed, and i’ve gained no new insight.

If it turns out to be wrong, though, that means my current understanding is flawed. That means I have to find the flaw and change my understanding of the world. That’s valuable. That means I’ve learned something new – that I’ve increased my total information.

Being proven right provides very little, if any, information; being proven wrong provides a lot. Strive to be correct, but hope to be wrong – it’s the best way to keep life interesting.

Abbey – don’t let the writing drive you crazy! I agree with a number of the comments above, if you did the experiments right then believe your data (I always hate grad students telling me that an experiment didn’t work – when what they mean is that is didn’t give them the result they expected). The expected results are never really interesting (just easier).

As you note being wrong is not a crime in science, it’s really a necessary consequence of being on the frontiers of knowledge. However being dishonest, while not so common, is a crime, and being either less than forthright – or aggressively overselling a result should be (at least in my opinion, overselling for short term gain can damage a whole field in the long term). You will eventually work out what the data are telling you – it just might not be the first, or second thing you think of.

I don’t know much about the academic research environment, but in learning mathematics, you have to be wrong. Being wrong, identifying and replicating your error so you can avoid it in the future might as well sum up the whole process. Getting right answers when you don’t really fully grasp the subject is probably the worst thing in the world, because you have no means of improving your understanding. The same goes for programming, in my experience.

Enrico Fermi once said (paraphrasing) that a scientist who has never been wrong is a scientist who has never accomplished anything. Even the most important scientists who have ever lived have been occasionally wrong.

Issac Newton was wrong in claiming that a particulate theory of light could explain diffraction and interference.

Charles Darwin was wrong in claiming that inheritance is an analog process.

Albert Einstein was wrong in claiming that black holes would never be formed.

On the other hand, those guys were right a hell of a lot more often then they were wrong and when they were right, their theories changed the world.

“A life spent making mistakes is not only more virtuous but more useful than one spent doing nothing” ~ George Bernard Shaw. He didn’t add “or one spent doing fuck all bar trolling comment threads belching up moronic conservative talking points”, but I trust you see his point.

Too many people who aren’t very familiar with how science works think of it as a system of received truth, rather than a highly methodical system of inquiry with a repeated cycle of hypothesis-and-testing.
And of course, received truth is never supposed to be wrong, so to them, wrong = FAIL.
But in an hypothesis-and-test cycle, a lot of the hypotheses are going to be wrong, because the “test” side of the cycle is supposed separate the ideas that don’t fly from the ones which require further investigation, so wrong = (at least a partial) WIN.
But flat-earthers and post-mod lit critics (is anybody willing to claim with a straight face that Derrida isn’t packaged as received truth?) have a hard time understanding this, made that much harder by their unwillingness to even try.

By which he meant, of course, that the paper to which he was referring was a masterpiece of intelligent-design theory, post-modernism, or both: it failed so utterly to frame a comprehensible, testable idea which bore some relation to observable phenomena that it could not contribute anything to a system of hypothesis-and-test-based inquiry.

And, of course, Sherlock Holmes (as channeled by the well-known spirit medium, Conan Doyle):
“…when you have eliminated the impossible, whatever remains, however improbable, must be the truth.”

The problem with that is that it is wrong — or rather, it’s only accurate in a simple, linear system. In the real world, it’s more like this:

That level of wrongness — when, for a moment, at least, there isn’t even an hypothesis to test, and it’s time to rethink the very basics of the situation — has produced, I think, some of the greatest and most far-reaching work in science.

While I’m sure everyone’s aware of this, I thought I’d mention the terrible damage and harm that can be caused by science which is wrong, especially if it feeds into the prejudices of society at the time.

Sometimes it won’t matter at all when you’re wrong, sometimes it will. The scientific process should help us correct these mistakes, but it doesn’t absolve responsibility for them.

When a scientific theory feeds into the prejudices of the times, it’s usually because the scientists involved are part of those times, and partake of those prejudices. That’s also true of the clergy (think of the theological justifications for slavery), of educators, of journalists, of anyone who, by profession or by professed beliefs, should be following a high standard of ethics.

Anyone who’s in a position to speak with the Voice of Authority (against which we should all plug our ears anyway) runs the risk of taking a wrong idea and turning it into received truth.

But authority and received truth aren’t part of the process of science as it’s supposed to be played; when they enter into science (which happens far more frequently than we might want to admit), it is as an intrusion from the larger world of human affairs, where politics, prejudice, dogma, and fear still, unfortunately, serve as common currency.

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Can’t understand how the dumb authors got a Nature review !!! Viruses are at the boundary… it’s like no-man’s land… if at all they had to classify, then live is the more sensible option!! Blah!

Posted by: chetana | October 2, 2009 1:39 AM

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Transformation of energy into a living matter needs a modus ssRNA, which creates a chain from simplest nucleotidal structures into dsDNA through eons, commenced in a primordial chemical soup producing bacterium, by their properties of being an antenna recepting information from the Cosmos how to shape about an organism capable to function in a given environment. Thus the most complex organism consists of “viruses” (RNA, DNA and bacteria – mitochondria), as structurally developed from viruses evolving into pro- and eurokaryotes, up to neurokaryotes, the latters the best suited colonies of viruses, as the humans are, which, being transformed from the energy into a matter, become capable to return into the Cosmos in an organized form and dominate the unorganized viruses, omnipresent over there. Hence capable of spreading across it the Cosmical Intelligence embeded into an Intelligent Homo Electronicus, the virusoidal colony. During the evolutionary path, from the simplest virus to Homo, does occur constant fight for primacy seen as invasion of viruses on any living creature and it will be lasting as long as Homos do not prevent such invasion on Earth and far beyond. So, viruses a part of the Tree of Life. Are Capsoided Life.